Variables of explanation: time, relating it to the price of your tech stock. Each of these multiple regression models for Set 1 contains 1 of the 5 time variables

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

GRADED MIDTERM EXAM   

I.  DIRECTIONS FOR THE GRADED MIDTERM EXAM

1.  You must e-mail the Graded Midterm Exam in a Word file to carpetfour@yahoo.com.  It is in place of (in lieu) of class on October 20 and 22. 

2.  Graded Midterm Exam is open book and open notes.

3.  Submission of answers only in Minitab 18.0 files, without defining your work in obtaining the solution in full, is not acceptable.  Detailed discussions must include the 

(a) business problem 

(b) data analysis techniques, 

(c) data, 

(d) analytical techniques, 

(e) computerized procedures, and 

(f) results and interpretation (per the course syllabus).  

4.  Merely providing screenshots from the Minitab 18.0 software is not acceptable. Rather they should be referenced in the results and interpretation. All computer output from Minitab 18.0 needs to be fully discussed and annotated. 

A. Multiple Regression Forecast Modeling Analysis of You Tech Company (Dependent Variable)

Using the first 30 months of data for the year starting in January 2017, 2018, and 2019, forecast the price of your tech stock for months 31, 32, and 33 in year 2019.  In all cases, the response variable is the price of your tech stock.   You need to indicate the name of your tech stock in your submission and your dataset.

In order to insure for validity of your Minitab Best Subsets regression computations, you must show a link between your Minitab data set, your Minitab Best Subsets regression drop downs, and your Minitab Best Subsets regression outputs.  That is, for each Best Subsets regression run, the data file, the drop down, and the output all need to be given.

B. Regression Models - Explanatory Variable Time Variables are the Independent Variables.

Set 1:  Variables of explanation: time, relating it to the price of your tech stock.  Each of these multiple regression models for Set 1 contains 1 of the 5 time variables.

1. time (t) (1, 2, ..., 30)      

2. time (t2) (1, 2, ..., 30)      

3. time [(1/t)] (1, 2, ..., 30)      

4. (sqt t) time (t-1, 2, ..., 30)

5. ln t time (t-1, 2, ..., 30)

. Multiple Regression Model – Finance Variables in the Dependent Variable

Set 2:  Variables of explanation:  finance, relating it to the price of your tech stock.  

1. Dow Jones Average (1, 2, ..., 30)

2. NASDQ Average (1, 2,.., 30)

3. S&P Average (1, 2,..., 30)

D. Multiple Regression Model:  Economic Variable Is the Independent Variable. 

1.  GDP (1, 2,..., 30)

2. Price of Oil Per Variable (1, 2,..., 30)

3. Unemployment Rate (1, 2,..., 30)

E. You will develop 3 Multiple Regression Models using Best Subsets Regression.

1.Model 1 – Relating the stock price of your tech stock (A) to time variables (B) and the finance variables (C) using Best Subsets Regression (first 30 months of data).

2.Model 2 – Relating the stock price of your tech stock (A) to time variables (B) and the economic variables (D) using Best Subsets regression (first 30 months of data).

3.Model 3 – Relating the stock price of your tech stock (A) to time variables (B) and the finance variables (C), and economic variables (D) using Best Subsets Regression (first 30 months of data).

 

 

F. Evaluation of Best Fit Model

For each of the three regression models in Model 1, 2, and 3, you need to display and discuss the models in terms of the best fit: 

R2, 

Mallow Cp statistic,

standard error of the model, 

coefficients, and 

coefficient standard errors.

G. Evaluation of the Forecasts

You need to evaluate and discuss the regression models in periods 31, 32, and 33 in terms of forecasting your tech stock price.

Attachments:

Related Questions

. The fundamental operations of create, read, update, and delete (CRUD) in either Python or Java

CS 340 Milestone One Guidelines and Rubric  Overview: For this assignment, you will implement the fundamental operations of create, read, update,

. Develop a program to emulate a purchase transaction at a retail store. This  program will have two classes, a LineItem class and a Transaction class

Retail Transaction Programming Project  Project Requirements:  Develop a program to emulate a purchase transaction at a retail store. This

. The following program contains five errors. Identify the errors and fix them

7COM1028   Secure Systems Programming   Referral Coursework: Secure

. Accepts the following from a user: Item Name Item Quantity Item Price Allows the user to create a file to store the sales receipt contents

Create a GUI program that:Accepts the following from a user:Item NameItem QuantityItem PriceAllows the user to create a file to store the sales receip

. The final project will encompass developing a web service using a software stack and implementing an industry-standard interface. Regardless of whether you choose to pursue application development goals as a pure developer or as a software engineer

CS 340 Final Project Guidelines and Rubric  Overview The final project will encompass developing a web service using a software stack and impleme